study guide -...

FRM STUDY GUIDE

2018

garp.org/frmFINANCIAL RISK MANAGER

2018 Financial Risk Manager (FRM®) Exam Study Guide

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2018 Financial Risk Manager (FRM®) Exam Study GuideThe world’s most highly respected designation for risk management professionals

TOPIC OUTLINE, READINGS, TEST WEIGHTINGSThe Study Guide sets forth primary topics and subtopics

covered in the FRM Exam Part I and Part II. The topics

were selected by the FRM Committee as essential for

today’s risk managers to master. The topics and their

respective weightings are reviewed yearly to ensure

the Exams are timely and relevant. The Study Guide

also contains a full listing of all of the readings that are

recommended as preparation for the FRM Exam Part I

and Part II.

Key concepts appear as bullet points at the beginning

of each section and are intended to help candidates

identify the major themes and knowledge areas

associated with that section.

FRM EXAM APPROACHThe FRM Exams are practice-oriented. The questions are

derived from a combination of theory, as set forth in the

readings, and “real-world” work experience. Candidates

are expected to understand risk management concepts

and approaches, as well as the ways in which they would

apply to a risk manager’s day-to-day activities. It is

rare that a risk manager will be faced with an issue that

can immediately be slotted into one category. In the

real world, a risk manager must be able to identify any

number of risk-related issues and be able to deal with

them effectively. As such, the Exams are comprehensive

in nature, testing a candidate on a number of risk

management concepts and approaches.

READINGSQuestions for the FRM Exams are related to and

supported by the readings listed under each topic

outline. These readings were selected by the FRM

Committee to assist candidates in their review of the

subjects covered by the Exams. It is strongly suggested

that candidates review these readings in depth prior to

sitting for each Exam. All of the readings listed in the

FRM Study Guide are available through GARP. Further

information can be found on the GARP website.

FRM EXAM PREP PROVIDERSSome candidates may want to more formally review the

materials with FRM Exam Preparation Providers (EPPs).

A list of EPPs that have registered with GARP can be

found on the GARP website. GARP does not endorse any

EPP but merely lists them as a service to FRM candidates.

On the following pages, an asterisk after a reading title indicates that the reading is freely available on the GARP website.

2 © 2018 Global Association of Risk Professionals.

Foundations of Risk ManagementPart I Exam Weight | 20%

Topics and Readings

This area focuses on foundational concepts of risk management and how risk management can add value to an

organization. The broad knowledge points covered in Foundations include the following:

} Basic risk types, measurement and management tools

} Creating value with risk management

} The role of risk management in corporate governance

} Enterprise Risk Management (ERM)

} Financial disasters and risk management failures

}The Capital Asset Pricing Model (CAPM)

} Risk-adjusted performance measurement

} Multifactor models

} Data aggregation and risk reporting

} Ethics and the GARP Code of Conduct

To cover these broad knowledge points, a set of curated readings is listed on the following page. While detailed

learning objectives associated with these readings are presented in the 2018 FRM Learning Objectives document, a

brief summary of how to relate these readings to the knowledge points follows.

Reading 1 contains three chapters with the first two giving a broad overview of risk, different risk types, and how

risks can arise in an organization. The third chapter describes the role of corporate governance in risk management

including the role of the board of directors and other areas of an organization. The concept of an organization’s risk

appetite and how this is translated into a risk appetite framework and communicated throughout an organization

is presented as well. Reading 2 introduces Enterprise Risk Management (ERM), a common and important method

for assessing and managing risk in an organizational context. Reading 3 focuses more specifically on risk taking by

banks and how risk management can add or destroy value in these institutions.

As it is always important to learn from history, the next several readings (Readings 4, 5, and 6) describe various

financial disasters from the past with a particular focus on the recent global financial crisis. Reading 7 gives a

nuanced approach to interpreting financial failures and the role that risk management may, or may not, have played

in them.

Reading 8 presents the Capital Asset Pricing Model (CAPM), one of the foundational developments in risk-adjusted

pricing and valuation. This is followed by a discussion, in Reading 9, of several commonly used CAPM-related risk

measures and their application to performance measurement. Reading 10 moves beyond CAPM and introduces

factor models and how they can be used to model returns.

Data is the lifeblood of many large financial organizations and aggregating and reporting risk data has become

increasingly important. Reading 11 addresses this important topic. To help ensure ethical standards are upheld in the

risk management profession, Reading 12 contains GARP’s Code of Conduct, a document that all FRMs are subject to.

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Readings for Foundations of Risk Management

1. Michel Crouhy, Dan Galai, and Robert Mark, The Essentials of Risk Management, 2nd Edition (New York, NY:

McGraw-Hill, 2014).

• Chapter 1. Risk Management: A Helicopter View (Including Appendix 1.1. Typology of Risk Exposures)

• Chapter 2. Corporate Risk Management: A Primer

• Chapter 4. Corporate Governance and Risk Management

2. James Lam, Enterprise Risk Management: From Incentives to Controls, 2nd Edition (Hoboken, NJ: John Wiley &

Sons, 2014).

• Chapter 4. What is ERM?

3. René Stulz, “Risk Management, Governance, Culture and Risk Taking in Banks,” FRBNY Economic Policy

Review, (August 2016): 43-59.

4. Steve Allen, Financial Risk Management: A Practitioner’s Guide to Managing Market and Credit Risk, 2nd Edition

(New York, NY: John Wiley & Sons, 2013).

• Chapter 4. Financial Disasters

5. Markus K. Brunnermeier, 2009. “Deciphering the Liquidity and Credit Crunch 2007—2008,” Journal of

Economic Perspectives 23:1, 77—100.

6. Gary Gorton and Andrew Metrick, 2012. “Getting Up to Speed on the Financial Crisis: A One-Weekend-

Reader’s Guide,” Journal of Economic Literature 50:1, 128—150.

7. René Stulz, “Risk Management Failures: What Are They and When Do They Happen?” Fisher College of

Business Working Paper Series, October 2008.

8. Edwin J. Elton, Martin J. Gruber, Stephen J. Brown and William N. Goetzmann, Modern Portfolio Theory and

Investment Analysis, 9th Edition (Hoboken, NJ: John Wiley & Sons, 2014).

• Chapter 13. The Standard Capital Asset Pricing Model

9. Noel Amenc and Veronique Le Sourd, Portfolio Theory and Performance Analysis (West Sussex, UK: John

Wiley & Sons, 2003).

• Chapter 4. Applying the CAPM to Performance Measurement: Single-Index Performance Measurement

Indicators (Section 4.2 only)

10. Zvi Bodie, Alex Kane, and Alan J. Marcus, Investments, 10th Edition (New York, NY: McGraw-Hill, 2013).

• Chapter 10. Arbitrage Pricing Theory and Multifactor Models of Risk and Return

11. “Principles for Effective Data Aggregation and Risk Reporting,” (Basel Committee on Banking Supervision

Publication, January 2013).

12. GARP Code of Conduct.*

* This reading is freely available on the GARP website.


Quantitative AnalysisPart I Exam Weight | 20%

Topics and Readings

This area tests a candidate’s knowledge of basic probability and statistics, regression and time series analysis, and

various quantitative techniques useful in risk management. The broad knowledge points covered in Quantitative

Analysis include the following:

} Discrete and continuous probability distributions

} Estimating the parameters of distributions

} Population and sample statistics

} Bayesian analysis

} Statistical inference and hypothesis testing

} Estimating correlation and volatility using EWMA and GARCH models

} Volatility term structures

} Correlations and copulas

} Linear regression with single and multiple regressors

} Time series analysis and forecasting

} Simulation methods




Reading 13 consists of five chapters. These chapters introduce basic, fundamental concepts related to probability,

statistics, probability distributions, Bayesian analysis, hypothesis testing, and confidence intervals.

Regression analysis is an important statistical tool used to investigate relationships between variables. The first

three chapters in Reading 14 give a general introduction to regression analysis. These chapters cover both single and

multiple variable linear regression analysis. The fourth chapter presents methods for quantifying the estimation error

associated with ordinary least squares regression and how to structure and evaluate tests of statistical hypotheses.

Time series data occur frequently in finance. The four chapters in Reading 15 describe methods for analyzing time

series data in order to estimate statistics and extract other meaningful characteristics of the data. The first chapter

focuses on modeling and forecasting trends. The second chapter focuses on modeling and forecasting seasonality.

The last two chapters focus on modeling cycles.

The two chapters in Reading 16 introduce volatility, correlation and copulas and how to use the EWMA model and the

GARCH(1,1) model to estimate future covariance and volatilities.

Simulation methods in finance are used to value and analyze complex financial instruments and portfolios. Reading

17 introduces simulation methods including Monte Carlo simulation and the use of the bootstrapping method. It also

explains the advantages and disadvantages of the simulation approach to financial problem solving and the

techniques to reduce Monte Carlo sampling error.

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13. Michael Miller, Mathematics and Statistics for Financial Risk Management, 2nd Edition (Hoboken, NJ: John Wiley

& Sons, 2013).

• Chapter 2. Probabilities

• Chapter 3. Basic Statistics

• Chapter 4. Distributions

• Chapter 6. Bayesian Analysis (Pages 113-124 only)

• Chapter 7. Hypothesis Testing and Confidence Intervals

14. James Stock and Mark Watson, Introduction to Econometrics, Brief Edition (Boston, MA: Pearson, 2008).

• Chapter 4. Linear Regression with One Regressor

• Chapter 5. Regression with a Single Regressor

• Chapter 6. Linear Regression with Multiple Regressors

• Chapter 7. Hypothesis Tests and Confidence Intervals in Multiple Regression

15. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, OH: Cengage Learning, 2006).

• Chapter 5. Modeling and Forecasting Trend

• Chapter 6. Modeling and Forecasting Seasonality

• Chapter 7. Characterizing Cycles

• Chapter 8. Modeling Cycles: MA, AR, and ARMA Models

16. John C. Hull, Risk Management and Financial Institutions, 4th Edition (Hoboken, NJ: John Wiley & Sons, 2015).

• Chapter 10. Volatility

• Chapter 11. Correlations and Copulas

17. Chris Brooks, Introductory Econometrics for Finance, 3rd Edition (Cambridge, UK: Cambridge University

Press, 2014).

• Chapter 13. Simulation Methods (Note: EViews and other programming references are not required.)

Readings for Quantitative Analysis


Financial Markets and ProductsPart I Exam Weight | 30%

Topics and Readings

This area tests your knowledge of financial products and the markets in which they trade, more specifically, the

following knowledge areas:

} Structures and functions of financial institutions

} Structure and mechanics of OTC and exchange markets

} Structure, mechanics, and valuation of forwards, futures, swaps, and options

} Hedging with derivatives

} Interest rates and measures of interest rate sensitivity

} Foreign exchange risk

} Corporate bonds

} Mortgage-backed securities

To cover these broad knowledge points, a set of curated readings is listed beginning on the following page. While

detailed learning objectives associated with these readings are presented in the 2018 FRM Learning Objectives

document, a brief summary of how to relate these readings to the knowledge points follows.

Reading 18 has three chapters. The first chapter describes the structure of commercial and investment banking, the

way banks are regulated, the nature of risks facing them, and the role of capital in providing cushion against losses.

The second chapter explains the risks and regulation faced by insurance companies, their capital requirements

and performance ratios, and the types and key characteristics of pension funds. The third chapter introduces

mutual funds and hedge funds, examines their key differences, and describes various hedge fund strategies and

performance measures.

Financial derivatives play a key role in risk management and their coverage is the basis of Reading 19, which has

eleven chapters. Chapters 1 through 3 describe options, forwards, and futures and explain the mechanics of futures

markets and central counterparties, and the hedging strategies using futures. Chapters 4 through 6 describe interest

rates and interest rate sensitivity, the determination of forward and futures prices, and the use of interest rate futures

in hedging. The mechanics, types, and the pricing of swaps contracts and the application of swaps for hedging are

described in Chapter 7. The next four chapters explain the mechanics of options markets, and the hedging strategies

involving options and exotic options. Reading 20 concludes the discussion on derivatives, defines basis risk,

describes commodity forwards and futures, explains the role of carry markets, and describes the determination of

the no-arbitrage values for commodity forwards and futures.

Reading 21 describes the structures and operations of central counterparties (CCPs). The exchange-traded and over-

the-counter (OTC) markets are explained along with the types of risks faced by CCPs. Reading 22 describes foreign

exchange risk and explains interest rate parity theorem, balance-sheet hedging, and the diversification benefits of

multicurrency asset-liability positions.

The last two readings examine two important classes of fixed income securities. Reading 23 describes corporate

bonds, their types and characteristics, and the distinctions between credit default risk and credit spread risk.

Reading 24 defines mortgages, explains the securitization process for mortgage-backed securities, and describes

prepayment modeling and the calculation of the various metrics for a typical mortgage pool.

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Readings for Financial Markets and Products


• Chapter 2. Banks

• Chapter 3. Insurance Companies and Pension Plans

• Chapter 4. Mutual Funds and Hedge Funds

19. John C. Hull, Options, Futures, and Other Derivatives, 10th Edition (New York, NY: Pearson, 2017).

• Chapter 1. Introduction

• Chapter 2. Futures Markets and central counterparties

• Chapter 3. Hedging Strategies Using Futures

• Chapter 4. Interest Rates

• Chapter 5. Determination of Forward and Futures Prices

• Chapter 6. Interest Rate Futures

• Chapter 7. Swaps

• Chapter 10. Mechanics of Options Markets

• Chapter 11. Properties of Stock Options

• Chapter 12. Trading Strategies Involving Options

• Chapter 26. Exotic Options

20. Robert McDonald, Derivatives Markets, 3rd Edition (Boston, MA: Addison-Wesley, 2013).

• Chapter 6. Commodity Forwards and Futures

21. Jon Gregory, Central Counterparties: Mandatory Clearing and Bilateral Margin Requirements for OTC

Derivatives (New York, NY: John Wiley & Sons, 2014).

• Chapter 2. Exchanges, OTC Derivatives, DPCs and SPVs

• Chapter 3. Basic Principles of Central Clearing

• Chapter 14. (section 14.4 only). Risks Caused by CCPs: Risks Faced by CCPs

22. Anthony Saunders and Marcia Millon Cornett, Financial Institutions Management: A Risk Management

Approach, 8th Edition (New York, NY: McGraw-Hill, 2014).

• Chapter 13. Foreign Exchange Risk

23. Frank Fabozzi (editor), The Handbook of Fixed Income Securities, 8th Edition (New York, NY: McGraw-Hill, 2012).

• Chapter 12. Corporate Bonds

24. Bruce Tuckman and Angel Serrat, Fixed Income Securities: Tools for Today’s Markets, 3rd Edition (Hoboken, NJ:

John Wiley & Sons, 2011).

• Chapter 20. Mortgages and Mortgage-Backed Securities


Valuation and Risk ModelsPart I Exam Weight | 30%

Topics and Readings

This area will test a candidate’s knowledge of valuation techniques and risk models. The broad knowledge points

covered in Valuation and Risk Models include the following:

} Value-at-Risk (VaR)

} Expected shortfall (ES)

} Stress testing and scenario analysis

} Option valuation

} Fixed income valuation

} Hedging

} Country and sovereign risk models and management

} External and internal credit ratings

} Expected and unexpected losses

} Operational risk




Reading 25 consists of two chapters that introduce Value-at-Risk (VaR) estimation approaches and applications.

Reading 26 covers financial risk measures and examines measurement frameworks such as the mean-variance

approach, VaR, and expected shortfall (ES).

The three chapters that comprise Reading 27 present the key elements of option pricing and option sensitivities.

Option valuation using binominal trees and the Black-Scholes-Merton model is covered, along with the use of options

for hedging and risk management.

The five chapters that form Reading 28 are devoted to valuing and understanding risk management for fixed income

securities. The first three chapters cover the various tools of fixed income valuation while the last two chapters cover

risk metrics and hedging.

Reading 29 explains the specific sources of country risk and the use of external ratings in assessing sovereign default

risk. A description of credit ratings, both external and internal, is further developed in the next reading. Reading 30

presents a review of external and internal rating methodologies and an assessment of the strengths and weaknesses

of the rating methodologies.

The next two readings foreshadow two very important exam topics covered in Part II. Reading 31 presents the basics

of credit risk, specifically expected loss (EL) and unexpected loss (UL) for both an individual security and a portfolio.

Reading 32 introduces various aspects of operational risk. Stress testing, its importance, applications, and practices

are explained in Readings 33 and 34.

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Readings for Valuation and Risk Models

25. Linda Allen, Jacob Boudoukh and Anthony Saunders, Understanding Market, Credit and Operational Risk: The

Value at Risk Approach (New York, NY: Wiley-Blackwell, 2004).

• Chapter 2. Quantifying Volatility in VaR Models

• Chapter 3. Putting VaR to Work

26. Kevin Dowd, Measuring Market Risk, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2005).

• Chapter 2. Measures of Financial Risk


• Chapter 13. Binomial Trees

• Chapter 15. The Black-Scholes-Merton Model

• Chapter 19. The Greek Letters



• Chapter 1. Prices, Discount Factors, and Arbitrage

• Chapter 2. Spot, Forward and Par Rates

• Chapter 3. Returns, Spreads and Yields

• Chapter 4. One-Factor Risk Metrics and Hedges

• Chapter 5. Multi-Factor Risk Metrics and Hedges

29. Aswath Damodaran, “Country Risk: Determinants, Measures and Implications - The 2017 Edition” (July 19, 2017).

(Pages 1-47 only).

30. Arnaud de Servigny and Olivier Renault, Measuring and Managing Credit Risk (New York, NY: McGraw-Hill,

2004).

• Chapter 2. External and Internal Ratings

31. Gerhard Schroeck, Risk Management and Value Creation in Financial Institutions (New York, NY: John Wiley &

Sons, 2002).

• Chapter 5. Capital Structure in Banks (Pages 170-186 only)


• Chapter 23. Operational Risk

33. Stress Testing: Approaches, Methods, and Applications, Edited by Akhtar Siddique and Iftekhar Hasan

(London, UK: Risk Books, 2013).

• Chapter 1. Governance over Stress Testing

• Chapter 2. Stress Testing and Other Risk Management Tools

34. “Principles for sound stress testing practices and supervision” (Basel Committee on Banking Supervision

Publication, May 2009).


Market Risk Measurement and ManagementPart II Exam Weight | 25%

Topics and Readings

This area focuses on market risk measurement and management techniques. The broad knowledge points covered in

Market Risk Measurement and Management include the following:

} VaR and other risk measures

• Parametric and non-parametric methods of estimation

• VaR mapping

• Backtesting VaR

• Expected shortfall (ES) and other coherent risk measures

} Modeling dependence: correlations and copulas

} Term structure models of interest rates

} Volatility: smiles and term structures




The importance of developing an understanding of VaR and other common risk measures used to assess risk cannot

be overstated. Reading 35 presents both parametric and non-parametric estimation techniques for VaR and ES.

Backtesting as a form of model validation as support for the use of VaR and VaR mapping as a tool to address

portfolio risk factors are presented in the two chapters of Reading 36. Reading 37 completes the risk measures

coverage by showing the uses and applications of VaR and ES in a trading book context and also addresses some of

the recent academic literature associated with market risk management.

Modern risk management requires an understanding of correlation risk. Reading 38 explains the basics of correlation

risk and explores the empirical properties, models, and modeling approaches related to correlation risk. The first

chapter covers the basics of correlation risk and how it is related to credit risk, market risk, systematic risk, and

concentration risk. The second chapter includes how correlations behave in different economic states as well as

mean reversion and autocorrelation. The third chapter demonstrates how to apply statistical correlation models.

The last chapter explains the purpose and uses of copula functions.

The five chapters in Reading 39 all are associated with term structure models and their impact on hedging. Various

regression hedges are explained in the first chapter. Term structure models that deal with drifts, mean reversions,

negative short-term rates, and time dependent volatilities are all reviewed. Specific term structure models, such as

the Ho-Lee, Vasicek, Cox-Ingersoll-Ross, and lognormal models are discussed in this reading.

Reading 40 covers very specific concepts related to the occurrence of volatility “smiles.”

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Readings for Market Risk Measurement and Management


• Chapter 3. Estimating Market Risk Measures: An Introduction and Overview

• Chapter 4. Non-parametric Approaches

36. Philippe Jorion, Value-at-Risk: The New Benchmark for Managing Financial Risk, 3rd Edition (New York, NY:

McGraw-Hill, 2007).

• Chapter 6. Backtesting VaR

• Chapter 11. VaR Mapping

37. “Messages from the academic literature on risk measurement for the trading book,” Basel Committee on

Banking Supervision, Working Paper No. 19, Jan 2011.

38. Gunter Meissner, Correlation Risk Modeling and Management (New York, NY: John Wiley & Sons, 2014).

• Chapter 1. Some Correlation Basics: Properties, Motivation, Terminology

• Chapter 2. Empirical Properties of Correlation: How Do Correlations Behave in the Real World?

• Chapter 3. Statistical Correlation Models—Can We Apply Them to Finance?

• Chapter 4. Financial Correlation Modeling—Bottom-Up Approaches (Sections 4.3.0 (intro), 4.3.1, and 4.3.2 only)



• Chapter 6. Empirical Approaches to Risk Metrics and Hedging

• Chapter 7. The Science of Term Structure Models

• Chapter 8. The Evolution of Short Rates and the Shape of the Term Structure

• Chapter 9. The Art of Term Structure Models: Drift

• Chapter 10. The Art of Term Structure Models: Volatility and Distribution


• Chapter 20. Volatility Smiles


Credit Risk Measurement and ManagementPart II Exam Weight | 25%

Topics and Readings

This area focuses on a candidate’s understanding of credit risk management, with some focus given to structured

finance and credit products such as collateralized debt obligations and credit derivatives. The broad areas of

knowledge covered in readings related to Credit Risk Management include the following:

} Credit analysis

} Default risk: Quantitative methodologies

} Expected and unexpected loss

} Credit VaR

} Counterparty risk

} Credit derivatives

} Structured finance and securitization




Reading 41 includes two chapters that introduce the key themes of credit risk management. The first chapter

discusses the components of credit risk, types of credit risk analysis, credit risk measurements, and factors that

cause credit risk. The second chapter describes various credit analyst roles and research skills expected of a credit

risk analyst. The role of ratings in supporting credit risk management and rating assignment methodologies are

discussed in the two chapters of Reading 42. The first chapter explains drivers and classifications of credit risk and

conditions necessary for value creation, subject to capital requirements. The second chapter describes the key

features of a good rating system, relates ratings to the probability of default, and analyzes different approaches to

predicting default. Reading 43 describes different approaches to credit risk modeling and assesses credit derivatives.

Reading 44 includes three chapters that cover portfolio and structured credit risk. The first chapter describes default

intensity models, explains credit spread risk, and defines the relationship between a default probability and a hazard

rate. The second chapter defines default correlation for credit portfolios and assesses the impact of correlation on

credit VaR. The third chapter describes common types of structured products, the mechanics of a securitization, and

explains how default sensitivities for tranches are measured.

Counterparty risk is covered in eight chapters that form Reading 45. The first three chapters identify ways of

managing and mitigating counterparty risk and describe the effects of netting, close-out, and collateral on

credit exposure. The fourth chapter describes credit exposure and funding, and this is followed by chapters on

counterparty risk intermediation and default probabilities, credit spreads, and funding costs. The last two chapters

cover the determination of credit exposure and the pricing of and exposure profiles for derivative contracts and two

chapters covering the analysis of credit and debt value adjustments and the concept of wrong-way risk. Reading 46

describes stress tests on CVA and the calculation of Debt Value Adjustment (DVA).

Reading 47 defines and compares the risk management and scoring models of retail and corporate credit risk.

Reading 48 describes Special Purpose Vehicles (SPVs) and explains performance analysis tools for securitized

structures. Finally, Reading 49 examines the subprime mortgage credit securitization process in the US and explains

the implications of credit ratings on subprime mortgage backed securities.

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Readings for Credit Risk Measurement and Management

41. Jonathan Golin and Philippe Delhaise, The Bank Credit Analysis Handbook, 2nd Edition (Hoboken, NJ: John

Wiley & Sons, 2013).

• Chapter 1. The Credit Decision

• Chapter 2. The Credit Analyst

42. Giacomo De Laurentis, Renato Maino, and Luca Molteni, Developing, Validating and Using Internal Ratings

(West Sussex, UK: John Wiley & Sons, 2010).

• Chapter 2. Classifications and Key Concepts of Credit Risk

• Chapter 3. Ratings Assignment Methodologies

43. René Stulz, Risk Management & Derivatives (Florence, KY: Thomson South-Western, 2002).

• Chapter 18. Credit Risks and Credit Derivatives

44. Allan Malz, Financial Risk Management: Models, History, and Institutions (Hoboken, NJ: John Wiley & Sons, 2011).

• Chapter 7. Spread Risk and Default Intensity Models

• Chapter 8. Portfolio Credit Risk (Sections 8.1, 8.2, 8.3 only)

• Chapter 9. Structured Credit Risk

45. Jon Gregory, The xVA Challenge: Counterparty Credit Risk, Funding, Collateral, and Capital (West Sussex, UK:


• Chapter 4. Counterparty Risk

• Chapter 5. Netting, Close-out and Related Aspects

• Chapter 6. Collateral

• Chapter 7. Credit Exposure and Funding

• Chapter 9. Counterparty Risk Intermediation

• Chapter 12. Default Probabilities, Credit Spreads, Funding Costs

• Chapter 14. Credit and Debt Value Adjustment

• Chapter 17. Wrong-way Risk

46. Stress Testing: Approaches, Methods, and Applications, Edited by Akhtar Siddique and Iftekhar Hasan

(London, UK: Risk Books, 2013).

• Chapter 4. The Evolution of Stress Testing Counterparty Exposures

47. Michel Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition (New York, NY:

McGraw-Hill, 2014).

• Chapter 9. Credit Scoring and Retail Credit Risk Management

• Chapter 12. The Credit Transfer Markets-and Their Implications

48. Moorad Choudhry, Structured Credit Products: Credit Derivatives & Synthetic Securitization, 2nd Edition

(New York, NY: John Wiley & Sons, 2010).

• Chapter 12. An Introduction to Securitization

49. Adam Ashcraft and Til Schuermann, “Understanding the Securitization of Subprime Mortgage Credit,” Federal

Reserve Bank of New York Staff Reports, No. 318 (March 2008).


Operational and Integrated Risk ManagementPart II Exam Weight | 25%

Topics and Readings

This area focuses on methods to measure and manage operational risk as well as methods to manage risk across

an organization, including risk governance, stress testing, and regulatory compliance. The broad knowledge points

covered in Operational and Integrated Risk Measurement and Management include the following:

} Principles for sound operational risk management

} Enterprise Risk Management (ERM) and

enterprise-wide risk governance

} IT infrastructure and data quality

} Internal and external operational loss data

} Methods of determining operational risk capital

for regulatory purposes

} Model risk and model validation

} Extreme value theory (EVT)

} Risk-adjusted return on capital (RAROC)

}Economic capital frameworks and capital planning

} Liquidity risk measurement and management

} Failure mechanics of dealer banks

} Stress testing banks

} Third-party outsourcing risk

} Risks related to money laundering and financing

of terrorism

} Regulation and the Basel Accords


detailed learning objectives associated with these readings are presented in the 2018 FRM Learning Objectives, a


Readings 50 through 53 cover operational risk governance and ERM, including recommended principles to manage

operational risk, governance principles for risk appetite frameworks, and data quality management. Readings 54 and

55 discuss methods of measuring and reporting operational losses and the use of internal and external operational

loss data. The second chapter in Reading 55 as well as Reading 56 present methods of measuring operational

risk capital recommended by the Basel Committee. (As there has recently been a major change proposed to this

approach, both the old methods are presented in Reading 55 as well as the new proposal in Reading 56.)

Readings 57 and 58 present issues related to modeling extreme losses, identifying and mitigating model risk, and

validating models. Reading 59 introduces capital planning and risk-adjusted return on capital, while readings 60 and

61 extend the discussion by presenting best practices in capital planning.

The important subject of liquidity risk is covered in Readings 62 through 64. This includes the use of repurchase

agreements, liquidity adjustments to VaR, and methods to manage funding and transactions liquidity risk. Readings

65 and 66 present a discussion of how banks can prepare for and respond to periods of financial distress, including

stress testing approaches. The section concludes with a discussion of regulatory guidelines and requirements,

including guidelines for managing outsourcing risk in Reading 67, an overview of the Basel regulations in Reading 68,

and risks related to money laundering and financing of terrorism in Reading 69. For the interested candidate, the full

Basel regulation documents are presented as optional readings.

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Readings for Operational and Integrated Risk Management

50. “Principles for the Sound Management of Operational Risk,” (Basel Committee on Banking Supervision

Publication, June 2011).

51. Brian Nocco and René Stulz, “Enterprise Risk Management: Theory and Practice,” Journal of Applied Corporate

Finance 18, No. 4 (2006): 8–20.

52. “Observations on Developments in Risk Appetite Frameworks and IT Infrastructure,” Senior Supervisors Group,

December 2010.

53. Anthony Tarantino and Deborah Cernauskas, Risk Management in Finance: Six Sigma and Other Next

Generation Techniques (Hoboken, NJ: John Wiley & Sons, 2009).

• Chapter 3: Information Risk and Data Quality Management

54. Marcelo G. Cruz, Gareth W. Peters, and Pavel V. Shevchenko, Fundamental Aspects of Operational Risk and

Insurance Analytics: A Handbook of Operational Risk (New York, NY: John Wiley & Sons, 2015).

• Chapter 2: OpRisk Data and Governance

55. Philippa X. Girling, Operational Risk Management: A Complete Guide to a Successful Operational Risk

Framework (Hoboken, NJ: John Wiley & Sons, 2013).

• Chapter 8. External Loss Data

• Chapter 12. Capital Modeling

56. “Standardised Measurement Approach for operational risk - consultative document,” (Basel Committee on

Banking Supervision Publication, March 2016).


• Chapter 7. Parametric Approaches (II): Extreme Value

58. Giacomo De Laurentis, Renato Maino, Luca Molteni, Developing, Validating and Using Internal Ratings

(Hoboken, NJ: John Wiley & Sons, 2010).

• Chapter 5. Validating rating models

59. Michel Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition (New York, NY:

McGraw-Hill, 2014).

• Chapter 15. Model Risk

• Chapter 17. Risk Capital Attribution and Risk-Adjusted Performance Measurement

60. “Range of practices and issues in economic capital frameworks,” (Basel Committee on Banking Supervision

Publication, March 2009).

61. “Capital Planning at Large Bank Holding Companies: Supervisory Expectations and Range of Current Practice,”

Board of Governors of the Federal Reserve System, August 2013.



• Chapter 12. Repurchase Agreements and Financing


Readings for Operational and Integrated Risk Management


• Chapter 14. Estimating Liquidity Risks

64. Allan Malz, Financial Risk Management: Models, History, and Institutions (Hoboken, NJ: John Wiley & Sons, 2011).

• Chapter 11. Assessing the Quality of Risk Measures (Section 11.1)

• Chapter 12. Liquidity and Leverage

65. Darrell Duffie, 2010. “The Failure Mechanics of Dealer Banks,” Journal of Economic Perspectives 24:1, 51-72.

66. Til Schuermann, “Stress Testing Banks,” prepared for the Committee on Capital Market Regulation, Wharton

Financial Institutions Center (April 2012).

67. “Guidance on Managing Outsourcing Risk,” Board of Governors of the Federal Reserve System, December 2013.

68. John Hull, Risk Management and Financial Institutions, 4th Edition (Hoboken, NJ: John Wiley & Sons, 2015).

• Chapter 15. Basel I, Basel II, and Solvency II

• Chapter 16. Basel II.5, Basel III, and Other Post-Crisis Changes

• Chapter 17. Fundamental Review of the Trading Book

This chapter references the December 2014 proposal for the Fundamental Review of the Trading Book. The final version

is “Minimum capital requirements for market risk” and is listed below as an Optional Regulatory Reading for Reference.

69. “Sound management of risks related to money laundering and financing of terrorism,” (Basel Committee on

Banking Supervision, June 2017). (Pages 1—32 only)

Optional Regulatory Readings for ReferenceCandidates are expected to understand the objective and general structure of important international regulatory

frameworks and general application of the various approaches for calculating minimum capital requirements, as

described in the readings above. Candidates interested in the complete regulatory framework can review the following:

“Basel II: International Convergence of Capital Measurement and Capital Standards: A Revised Framework—

Comprehensive Version,” (Basel Committee on Banking Supervision Publication, June 2006).*

“Basel III: A global regulatory framework for more resilient banks and banking systems—revised version,” (Basel

Committee on Banking Supervision Publication, June 2011).*

“Basel III: The Liquidity Coverage Ratio and liquidity risk monitoring tools,” (Basel Committee on Banking

Supervision Publication, January 2013).*

“Revisions to the Basel II market risk framework—updated as of 31 December 2010,” (Basel Committee on Banking

Supervision Publication, February 2011).*

“Basel III: The net stable funding ratio.” (Basel Committee on Banking Supervision Publication, October 2014).*

“Minimum capital requirements for market risk” (Basel Committee on Banking Supervision Publication,

January 2016).*

*This reading is freely available on the GARP website.


garp.org/frm 17

Risk Management and Investment ManagementPart II Exam Weight | 15%

Topics and Readings

This area focuses on investment management concepts of risk management techniques applied to the investment

management process. The broad knowledge points covered in Investment Management and Risk Management

include the following:

} Factor theory

} Portfolio construction

} Portfolio risk measures

} Risk budgeting

} Risk monitoring and performance measurement

} Portfolio-based performance analysis

} Hedge funds




Reading 70 introduces the factor theory of investing, in which asset and portfolio returns and risk premiums are

explained by their exposure to specific factors. The first chapter describes the theory of factor risk by starting

with the basic single-factor risk premium theory – the CAPM. The chapter then transitions into multifactor models.

The second chapter explains factors that drive risk premiums and compares two types of factors: fundamental-

based factors and investment-style factors. The third chapter explores how the sets of factors used to construct a

benchmark can affect portfolio alpha. The final chapter focuses on challenges in measuring performance for illiquid

assets, including potential biases in illiquid asset classes’ risk-adjusted returns and ways to address illiquidity in

performance reporting.

Reading 71 introduces ways to construct an optimal portfolio given investment constraints.

Value-at-Risk (VaR) is an important tool in portfolio management as it explicitly accounts for leverage and portfolio

diversification and provides a single measure of portfolio risk. The first chapter of Reading 72 explains how managers

can measure and manage portfolio VaR. The second chapter explains some benefits of using VaR in investment

management and introduces the process of risk budgeting.

As risk capital is a scarce resource, controls should exist to ensure that risk capital is used in a manner consistent

with the firm’s risk budget. Reading 73 explains how managers can develop a risk plan, provides some tools for risk

budgeting, and introduces some guidelines for monitoring portfolio risk.

Standardized measurements are helpful for investors in comparing the performance of asset managers. Reading 74

introduces various measures to evaluate the performance of portfolio managers.

Hedge funds are private investment vehicles not open to the general investing public. Reading 75 gives a general

introduction to hedge fund styles and Reading 76 describes the process of performing due diligence on funds and

fund managers as part of the investment process.

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Readings for Risk Management and Investment Management

70. Andrew Ang, Asset Management: A Systematic Approach to Factor Investing (New York, NY: Oxford University

Press, 2014).

• Chapter 6. Factor Theory

• Chapter 7. Factors

• Chapter 10. Alpha (and the Low-Risk Anomaly)

• Chapter 13. Illiquid Assets

71. Richard Grinold and Ronald Kahn, Active Portfolio Management: A Quantitative Approach for Producing

Superior Returns and Controlling Risk, 2nd Edition (New York, NY: McGraw-Hill, 2000).

• Chapter 14. Portfolio Construction

72. Philippe Jorion, Value-at-Risk: The New Benchmark for Managing Financial Risk, 3rd Edition (New York, NY:

McGraw Hill, 2007).

• Chapter 7. Portfolio Risk: Analytical Methods

• Chapter 17. VaR and Risk Budgeting in Investment Management

73. Robert Litterman and the Quantitative Resources Group, Modern Investment Management: An Equilibrium

Approach (Hoboken, NJ: John Wiley & Sons, 2003).

• Chapter 17. Risk Monitoring and Performance Measurement

74. Zvi Bodie, Alex Kane, and Alan J. Marcus, Investments, 10th Edition (New York, NY: McGraw-Hill, 2013).

• Chapter 24. Portfolio Performance Evaluation

75. G. Constantinides, M. Harris and R. Stulz, eds., Handbook of the Economics of Finance, Volume 2B (Oxford, UK:

Elsevier, 2013).

• Chapter 17. Hedge Funds

76. Kevin R. Mirabile, Hedge Fund Investing: A Practical Approach to Understanding Investor Motivation, Manager

Profits, and Fund Performance, 2nd Edition (Hoboken, NJ: John Wiley & Sons, 2016).

• Chapter 12. Performing Due Diligence on Specific Managers and Funds


garp.org/frm 19

Current Issues in Financial MarketsPart II Exam Weight | 10%

Topics and Readings

This area of the Exam will test a candidate’s knowledge of the material covered by each paper. The broad knowledge

points covered in Current Issues include the following:

} Credit loss provisioning, IFRS 9/CECL

} Machine learning and “big data”

} Central clearing and risk transformation

} The failure of covered interest rate parity

} FinTech credit

} Corporate culture




Reading 77 presents an overview of rules on loan loss provisioning standards and practices adopted by two major accounting

standard-setting bodies. The International Accounting Standards Board published the final version of International Financial

Reporting Standard 9 (IFRS 9) in 2014, and the US Financial Accounting Standards Board published its final provisioning

standard on “Current Expected Credit Losses” (CECL) in 2016. The reasons for provisioning expected credit losses,

the progress in banks’ implementation of these standards, and the impact on the financial system are considered.

Reading 78 focuses on the issues unique to big datasets and the different tools that may be required to manipulate and analyze

big data. Opportunities and areas for collaboration between econometrics and machine learning are discussed, including

causality and prediction. Machine learning methods to analyze large amounts of data and the application of machine learning

approaches within the financial services sector are further discussed in Reading 79. A background of machine learning and an

overview of machine learning methods are presented, and three areas of machine learning use are explored in this reading.

The next reading examines how the clearing of over-the-counter transactions through Central Counterparties (CCPs)

has affected risks in the financial system and whether central clearing has enhanced financial stability and reduced

systemic risk. Reading 80 discusses the transformation of counterparty risk into liquidity risk. An argument is made

that the main focus of risk management and financial stability analysis should be on the liquidity of clearing members

and the liquidity resources of CCPs.

Reading 81 argues that the link between banks and capital markets has gone global. Forced deleveraging and the

failure of Covered Interest Parity (CIP) are reviewed, followed by a discussion of the US dollar’s role as the measure

of the appetite for leverage, and the implications of a stronger dollar on financial stability and the real economy.

FinTech credit is the focus of Reading 82, particularly a study on how FinTech credit markets are likely to develop

and how they will affect the nature of credit provision and the traditional banking sector. The study analyzes the

functioning of FinTech credit markets and activities, assesses the potential microfinancial benefits and risks of these

activities, and considers the implications for financial stability in the event that FinTech credit grows to account for a

significant share of overall credit.

Reading 83 examines the role of culture in the context of financial risk management. The reading describes a specific

framework for analyzing culture in the context of financial practices and institutions, and the importance of culture

and whether it can be changed are addressed by applying the framework to five concrete situations.

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Readings for Current Issues in Financial Markets

77. Cohen, Benjamin H. and Gerald A. Edwards, Jr., “The new era of expected credit loss provisioning,” BIS

Quarterly Review, March 20, 2017.*

78. Varian, Hal, “Big Data: New Tricks for Econometrics,” Journal of Economic Perspectives 28:2 (Spring 2014), 3-28.*

79. van Liebergen, Bart, “Machine Learning: A Revolution in Risk Management and Compliance?” Institute of

International Finance, April 2017.*

80. Cont, Rama, “Central clearing and risk transformation,” Norges Bank Research, March 2017.*

81. Song Shin, Hyun, “The bank/capital markets nexus goes global,” BIS Quarterly Review, November 2016.*

82. “FinTech credit: Market structure, business models and financial stability implications.” BIS—Committee on

Global Financial Systems, May 2017.*

83. Lo, Andrew W., “The Gordon Gekko Effect: The Role of Culture in the Financial Industry,” Federal Reserve Bank

of New York Economic Policy Review, 22:1 (August 2016).*

* This reading is freely available on the GARP website.


garp.org/frm 21

2018 FRM Committee Members

Dr. René Stulz, Chairman ..................................................... Everett D. Reese Chair of Banking and Monetary Economics

The Ohio State University

Richard Apostolik ................................................................... President and CEO, Global Association of Risk Professionals

Michelle McCarthy Beck ...................................................... EVP, CRO, Nuveen

Richard Brandt ........................................................................ MD, Operational Risk Management, Citigroup

Dr. Christopher Donohue .................................................... MD, Global Association of Risk Professionals

Hervé Geny ............................................................................... Group Head of Internal Audit, London Stock Exchange Group

Keith Isaac, FRM ..................................................................... VP, Capital Markets Risk Management, TD Bank Group

William May .............................................................................. SVP, Global Association of Risk Professionals

Dr. Attilio Meucci, CFA ......................................................... Founder, ARPM; Partner, Oliver Wyman

Dr. Victor Ng ........................................................................... MD, Chief Risk Architect, Market Risk Management and Analysis

Goldman Sachs

Dr. Matthew Pritsker .............................................................. Senior Financial Economist and Policy Advisor

Supervision, Regulation, and Credit, Federal Reserve Bank of Boston

Dr. Samantha C. Roberts, FRM .......................................... SVP, Retail Credit Modeling, PNC

Liu Ruixia ................................................................................... Head of Risk Management, Industrial and Commercial Bank of China

Dr. Til Schuermann ................................................................. Partner, Oliver Wyman

Nick Strange, FCA.................................................................. Head of Risk Infrastructure, Bank of England

Prudential Regulation Authority

Dr. Sverrir Þorvaldsson, FRM ............................................. CRO, Islandsbanki

© 2018 Global Association of Risk Professionals. All rights reserved. (11.14.17)

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Creating a culture of risk awareness®

The Global Association of Risk Professionals (GARP) is the leading

association dedicated to the education and certification of risk

professionals, connecting members in more than 190 countries and

territories. GARP’s mission is to elevate the practice of risk management

at all levels, setting the industry standard through education, training,

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